Authors:
Srinidhi Kulkarni, Manjula Sanjay Koti, S. Priyadarshini, G. Rajasekaran, Prasanna Ranjith Christodoss
Addresses:
Department of Computer Application, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India. Department of Computer Science and Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Computing, Mathematics and Physics, Messiah University, One University Ave, Mechanicsburg, Pennsylvania, United States of America.
Abstract:
Frameworks are taking over new web app development, growth, and success in the future of web development. The research paper illustrates a comparison between front-end and back-end frameworks, i.e., React, Angular, Vue.js, Django, Spring, and Express.js, based on the findings of recent studies. Test data are available in synthetically generated Framework Performance Benchmark (FPB) data. The Pandas Python package provides data manipulation, and Matplotlib/Seaborn provides visualisations. Outcomes to a significant degree are so. Front-end component-based system frameworks best serve maintainability and reusability. Open-source community contributions and quality documentation are the appropriate adoption recipes. Third, with agile project frameworks and prototyping, some facilitate support, maintenance and scalability and thus context-dependent form selection. Practice implications are also supported by case studies showing their impact on project efficiency and performance. The research concludes that developers must utilise not only technical but also contextual environment variables, such as adequate documentation and communal support, when using SCM. The article therefore provides developers and decision-makers with a point of reference for making informed decisions on the frameworks' approaches to achieving optimal innovation, sustainability, and web application development performance.
Keywords: Back-End Frameworks; Front-End Frameworks; Performance Analysis; Software Engineering; Web Development; Framework Performance Benchmark (FPB); Open-Source Community.
Received: 16/07/2024, Revised: 30/08/2024, Accepted: 11/10/2024, Published: 03/06/2025
DOI: 10.64091/ATICL.2025.000149
AVE Trends in Intelligent Computer Letters, 2025 Vol. 1 No. 2 , Pages: 86-94